Published November 22, 2023 | Version v1
Dataset Open

Scalable SAT Solving and its Application | Experimental Data

  • 1. Karlsruher Institut für Technologie

Description

Experimental data accompanying the doctoral thesis of Dominik P. Schreiber entitled "Scalable SAT Solving and its Application", Karlsruhe Institute of Technology, 2023.

Upstream URL: https://github.com/domschrei/sssaia

--

Funding notices:

This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 882500).

Some of this work was performed on the supercomputer ForHLR funded by the Ministry of Science, Research and the Arts Baden-W ̈urttemberg and by the Federal Ministry of Education and Research.

Some of this work was performed on the HoreKa supercomputer funded by the Ministry of Science, Research and the Arts Baden-Württemberg and by the Federal Ministry of Education and Research.

The author gratefully acknowledges the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de).

Files

sssaia.zip

Files (104.1 MB)

Name Size Download all
md5:48ebb46b3455bf47855f3fbd3a047664
104.1 MB Preview Download

Additional details

Related works

Is version of
Dataset: https://github.com/domschrei/sssaia (URL)